CN105606977B - Shelf depreciation PRPS spectrum recognition method and system based on hierarchical rule reasoning - Google Patents
Shelf depreciation PRPS spectrum recognition method and system based on hierarchical rule reasoning Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The shelf depreciation PRPS spectrum recognition method and system based on hierarchical rule reasoning that the present invention provides a kind of, including step 1: detecting the local discharge signal of power equipment, obtain PRPS map；Step 2: the PRPS data in PRPS map being handled, PRPS characteristic parameter is obtained；Step 3: PRPS characteristic parameter being analyzed by hierarchical rule reasoning diagnostic system, judgement obtains the shelf depreciation type of power equipment.The present invention can effectively identify all kinds of local discharge signals and noise signal type, simplicity is accurately diagnosed to be the shelf depreciation mode of power equipment, provides reliable basis for the insulation condition diagnosis of power equipment by doing unified standard processing to shelf depreciation PRPS map.
Description
Technical field
The present invention relates to Fault Diagnosis for Electrical Equipment fields, and in particular, to a kind of part based on hierarchical rule reasoning
Electric discharge PRPS (Phase Resolved Pulse Sequence, nervuration phase characteristic) spectrum recognition method.
Background technique
The main reason for shelf depreciation is the important characterization of Electric Power Equipment Insulation failure, and insulation further deteriorates.Office
The factor that portion's electric discharge damages effect to insulation includes the chemistry of thermodynamic activity, the bombardment with point particle, shelf depreciation generation
Effect, mechanical effect and the shock wave of active matter and the effect of radiation.These factors often exist simultaneously, cause corrode and
Variation in structure destroys the insulation performance of electrical equipment to change the electrically and mechanically intensity of medium.
Shelf depreciation can generate a series of light, sound, vibration electrically and mechanically in space inside and around power equipment
Etc. physical phenomenons and chemical change.These various physical and chemical changes occurred with shelf depreciation can be detection electric power
Apparatus insulated state provides detection signal.According to the difference of testing principle and detection means, common detection method for local discharge
There are transient earth voltage method, superfrequency method, supercritical ultrasonics technology and high-frequency current coupled method etc., the Partial Discharge Data type usually detected
Including time-domain signal, frequency-region signal, pulse train, phase profile data, electric discharge fingerprint and picture etc..Due to local at present
Discharge test device and technology are different, lack unified data standard, and being compared to each other for test result is not utilized to test with history
Data exchange.
Different shelf depreciation processes have differences, and can judge office by the signal characteristic difference of all kinds of shelf depreciations
Portion's electric discharge type.Each shelf depreciation type influences severity difference to the insulation performance of equipment, is high-tension switch gear therefore
Equipment carries out Partial Discharge Detection, and standardization detection data record judges shelf depreciation type, to maintain equipment safety and electric power
System stable operation is of great significance to.
Summary of the invention
For the defects in the prior art, the object of the present invention is to provide a kind of shelf depreciations based on hierarchical rule reasoning
PRPS spectrum recognition method and system.
The shelf depreciation PRPS spectrum recognition method based on hierarchical rule reasoning provided according to the present invention, including walk as follows
It is rapid:
Step 1: detecting the local discharge signal of power equipment, obtain PRPS map；
Step 2: PRPS spectrum data being handled, PRPS characteristic parameter is obtained；
Step 3: PRPS characteristic parameter being analyzed by hierarchical rule reasoning diagnostic system, judgement obtains power equipment
Shelf depreciation type.
Preferably, the step 1 includes: the shelf depreciation letter that power equipment is acquired by a variety of partial discharge detector's devices
Number, specifically, using the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit, detect the office of power equipment
Portion's discharge signal records PRPS map.
Preferably, the step 2 includes:
Step 2.1: PRPS spectrum data being normalized, by electric discharge amplitude reduction into [0,1] section；Normalizing
It is as follows to change the method calculated:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates amplitude measurement section most
Small value, max indicate the maximum value in amplitude test section；
The denoising of step 2.2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS pulse point
Incidence relation between cloth data, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, time
The small threshold value ambient noise of cloth refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Step 2.3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method,
Make signal that there is complete characterization in the distribution of the first, second, third and fourth quadrant of discharge phase；Wherein, adaptive phase adjusting method refers to
According to distribution of the PRPS map in phase, adjust automatically phase offset；
Step 2.4:PRPS characteristic parameter extraction counts discharge time phase distribution, the electric discharge amplitude phase of PRPS map
Distribution, discharge time period profile, obtain discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree
With these PRPS characteristic parameters of dispersion degree.
Preferably, the step 3 includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained, defeated
The confidence level of every kind of signal type is obtained out, obtains diagnosis after statistics.
Preferably, the hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer
And signal type layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal point
Cluster number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal,
Every kind of signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation for sequentially judge signal characteristic in input signal and signal characteristic layer,
Export the confidence level of every kind of signal type.
The shelf depreciation PRPS spectrum recognition system based on hierarchical rule reasoning provided according to the present invention, comprising:
Detection module obtains PRPS map for detecting the local discharge signal of power equipment；
Data processing module obtains PRPS characteristic parameter for handling PRPS spectrum data；
Diagnostic module, for being analyzed by hierarchical rule reasoning diagnostic system PRPS characteristic parameter, judgement is obtained
The shelf depreciation type of power equipment.
Preferably, the detection module includes: to be put by the part that a variety of partial discharge detector's devices acquire power equipment
Electric signal specifically using the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit, detects power equipment
Local discharge signal, record PRPS map.
Preferably, the data processing module includes:
Submodule 1: being normalized PRPS spectrum data, by electric discharge amplitude reduction into [0,1] section；Normalizing
It is as follows to change the method calculated:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates amplitude measurement section most
Small value, max indicate the maximum value in amplitude test section；
The denoising of submodule 2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS pulse point
Incidence relation between cloth data, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, time
The small threshold value ambient noise of cloth refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Submodule 3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method,
Make signal that there is complete characterization in the distribution of the first, second, third and fourth quadrant of discharge phase；Wherein, adaptive phase adjusting method refers to
According to distribution of the PRPS map in phase, adjust automatically phase offset；
Submodule 4:PRPS characteristic parameter extraction counts discharge time phase distribution, the electric discharge amplitude phase of PRPS map
Distribution, discharge time period profile, obtain discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree
With these PRPS characteristic parameters of dispersion degree.
Preferably, the diagnostic module includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained,
Output obtains the confidence level of every kind of signal type, obtains diagnosis after statistics.
Preferably, the hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer
And signal type layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal point
Cluster number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal,
Every kind of signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation for sequentially judge signal characteristic in input signal and signal characteristic layer,
Export the confidence level of every kind of signal type.
Compared with prior art, the present invention have it is following the utility model has the advantages that
1, the shelf depreciation PRPS spectrum recognition method provided by the invention based on hierarchical rule reasoning is by putting part
Electric PRPS map does unified standard processing, can effectively identify all kinds of local discharge signals and noise signal type.
2, the shelf depreciation PRPS spectrum recognition method provided by the invention based on hierarchical rule reasoning can be easy to be accurate
Ground identifies the shelf depreciation mode of power equipment, provides reliable basis for the insulation condition diagnosis of power equipment.
Detailed description of the invention
Upon reading the detailed description of non-limiting embodiments with reference to the following drawings, other feature of the invention,
Objects and advantages will become more apparent upon:
Fig. 1 is the overall procedure of the shelf depreciation PRPS spectrum recognition method provided by the invention based on hierarchical rule reasoning
Figure；
Fig. 2 is the PRPS map signal of typical shelf depreciation (corona).
Specific embodiment
The present invention is described in detail combined with specific embodiments below.Following embodiment will be helpful to the technology of this field
Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill of this field
For personnel, without departing from the inventive concept of the premise, several changes and improvements can also be made.These belong to the present invention
Protection scope.
The shelf depreciation PRPS spectrum recognition method based on hierarchical rule reasoning provided according to the present invention, including walk as follows
It is rapid:
Step 1: detecting the local discharge signal of power equipment, obtain PRPS map；
Step 2: PRPS spectrum data being handled, PRPS characteristic parameter is obtained；
Step 3: PRPS characteristic parameter being analyzed by hierarchical rule reasoning diagnostic system, judgement obtains power equipment
Shelf depreciation type.
The step 1 includes: the local discharge signal that power equipment is acquired by a variety of partial discharge detector's devices, specifically
The shelf depreciation letter of power equipment is detected using the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit in ground
Number, record PRPS map.
The step 2 includes:
Step 2.1: PRPS spectrum data being normalized, by electric discharge amplitude reduction into [0,1] section；Normalizing
It is as follows to change the method calculated:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates amplitude measurement section most
Small value, max indicate the maximum value in amplitude test section；
The denoising of step 2.2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS pulse point
Incidence relation between cloth data, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, time
The small threshold value ambient noise of cloth refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Step 2.3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method,
Make signal that there is complete characterization in the distribution of the first, second, third and fourth quadrant of discharge phase；Wherein, adaptive phase adjusting method refers to
According to distribution of the PRPS map in phase, adjust automatically phase offset；
Step 2.4:PRPS characteristic parameter extraction counts discharge time phase distribution, the electric discharge amplitude phase of PRPS map
Distribution, discharge time period profile, obtain discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree
With these PRPS characteristic parameters of dispersion degree.
The step 3 includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained, and output obtains every
The confidence level of signal type is planted, obtains diagnosis after statistics.
The hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer and signal
Type layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal point
Cluster number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal,
Every kind of signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation for sequentially judge signal characteristic in input signal and signal characteristic layer,
Export the confidence level of every kind of signal type.
The shelf depreciation PRPS spectrum recognition system based on hierarchical rule reasoning provided according to the present invention, comprising:
Detection module obtains PRPS map for detecting the local discharge signal of power equipment；
Data processing module obtains PRPS characteristic parameter for handling PRPS spectrum data；
Diagnostic module, for being analyzed by hierarchical rule reasoning diagnostic system PRPS characteristic parameter, judgement is obtained
The shelf depreciation type of power equipment.
The detection module includes: the local discharge signal that power equipment is acquired by a variety of partial discharge detector's devices,
Specifically, using the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit, the part for detecting power equipment is put
Electric signal records PRPS map.
The data processing module includes:
Submodule 1: being normalized PRPS spectrum data, by electric discharge amplitude reduction into [0,1] section；Normalizing
It is as follows to change the method calculated:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates amplitude measurement section most
Small value, max indicate the maximum value in amplitude test section；
The denoising of submodule 2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS pulse point
Incidence relation between cloth data, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, time
The small threshold value ambient noise of cloth refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Submodule 3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method,
Make signal that there is complete characterization in the distribution of the first, second, third and fourth quadrant of discharge phase；Wherein, adaptive phase adjusting method refers to
According to distribution of the PRPS map in phase, adjust automatically phase offset；
Submodule 4:PRPS characteristic parameter extraction counts discharge time phase distribution, the electric discharge amplitude phase of PRPS map
Distribution, discharge time period profile, obtain discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree
With these PRPS characteristic parameters of dispersion degree.
The diagnostic module includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained, and is exported
To the confidence level of every kind of signal type, diagnosis is obtained after statistics.
The hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer and signal
Type layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal point
Cluster number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal,
Every kind of signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation for sequentially judge signal characteristic in input signal and signal characteristic layer,
Export the confidence level of every kind of signal type.
Specifically, as shown in Figure 1, including the following steps:
Step S1: detecting the local discharge signal of power equipment, obtains PRPS map；
Local discharge signal can be acquired by various partial discharge detector's devices, records the data of diversified forms, specifically
Ground uses in the present embodiment China to multiply superfrequency, ultrasound and the high-frequency current of electrical PDS-T90 hand-held instrument for measuring partial discharge
Detection unit detects the local discharge signal of power equipment, records PRPS map.Wherein, the PDS-T90 hand-held is locally put
Electric tester includes main processor unit, data collecting card, memory module, communication management module and human-computer interaction module.Data
Capture card is connected with ultrahigh-frequency signal detection unit, ultrasonic signal detection unit, high-frequency current detection unit.Use hand-held
Superfrequency, ultrasound and the high-frequency current detection unit of instrument for measuring partial discharge, detect the local discharge signal of power equipment, record
PRPS spectrum data.PRPS spectrum data is as shown in Figure 2.PRPS refers to phase-period-electric discharge amplitude data, indicates each period
On electric discharge amplitude phase distribution.
Step S2: the PRPS data in PRPS map are handled, PRPS characteristic parameter is obtained；Specifically, comprising:
Step S2.1: being normalized PRPS map, by electric discharge amplitude reduction to [0,1] section；The step has
Conducive to standardization different meter device recorded data, the amplitude measurement data of the units such as pC, mV, dB, dBm are done and are uniformly returned
It calculates.
The denoising of step S2.2:PRPS map, removes ambient noise and scattered interference signal；I.e. according to PRPS distribution of pulses number
Incidence relation between, removes scattered random interfering signal, at the same to throughout small threshold value ambient noise filter out.
Step S2.3:PRPS phase alignment；It is different surely to get accurate source of synchronising signal when detecting at the scene, because
This, does phase alignment to PRPS map using adaptive phase adjusting method in the step, make signal discharge phase first,
Two, three, four-quadrant distribution has complete characterization.
Step S2.4:PRPS characteristic parameter extraction counts discharge time phase distribution, the electric discharge amplitude phase of PRPS map
Distribution, discharge time period profile calculate discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree
With the PRPS characteristic parameter such as dispersion degree.
Step S3: analyzing PRPS characteristic parameter by hierarchical rule reasoning diagnostic system, and judgement obtains electric power and sets
Standby shelf depreciation type；Specifically,
Obtained PRPS characteristic parameter is inputted into hierarchical rule reasoning diagnostic system, output obtains setting for every kind of signal type
Reliability, statistics obtain the diagnosis of target data.Wherein, hierarchical rule reasoning diagnostic system is divided into following four layers:
A, foundation characteristic layer characterizes the bottom signal characteristic of map；Foundation characteristic includes: number of signals section, signal
The parameters such as sub-clustering number, the electric discharge degree of correlation, electric discharge amplitude fluctuations.
B, linked character layer does association analysis according to the similitude of each foundation characteristic.
C, signal characteristic layer, there are many signal characteristics to show for every class signal, and every kind of signal characteristic is the group of linked character layer
It closes.
D, signal type layer, sequence judge meet situation of the input signal with signal characteristic layer, export every kind of signal type
Confidence level.
The present invention can effectively identify all kinds of local discharge signals by doing unified standard processing to shelf depreciation PRPS map
With noise signal type, provides the convenience of PD Pattern Recognition and effective method, be conducive to the insulation of power equipment
Status assessment diagnosis.
One skilled in the art will appreciate that in addition to realizing system provided by the invention in a manner of pure computer readable program code
And its other than each device, completely can by by method and step carry out programming in logic come so that system provided by the invention and its
Each device is in the form of logic gate, switch, specific integrated circuit, programmable logic controller (PLC) and embedded microcontroller etc.
To realize identical function.So system provided by the invention and its every device are considered a kind of hardware component, and it is right
The device for realizing various functions for including in it can also be considered as the structure in hardware component；It can also will be for realizing each
The device of kind function is considered as either the software module of implementation method can be the structure in hardware component again.
Specific embodiments of the present invention are described above.It is to be appreciated that the invention is not limited to above-mentioned
Particular implementation, those skilled in the art can make a variety of changes or modify within the scope of the claims, this not shadow
Ring substantive content of the invention.In the absence of conflict, the feature in embodiments herein and embodiment can any phase
Mutually combination.
Claims (6)
1. a kind of shelf depreciation PRPS spectrum recognition method based on hierarchical rule reasoning, which comprises the steps of:
Step 1: detecting the local discharge signal of power equipment, obtain PRPS map；
Step 2: PRPS spectrum data being handled, PRPS characteristic parameter is obtained；
Step 3: PRPS characteristic parameter being analyzed by hierarchical rule reasoning diagnostic system, judgement obtains the office of power equipment
Portion's electric discharge type；
Wherein, the step 3 includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained, and output obtains
The confidence level of every kind of signal type obtains diagnosis after statistics；
The hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer and signal type
Layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal sub-clustering
Number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal, and every kind
Signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation, output for sequentially judge signal characteristic in input signal and signal characteristic layer
The confidence level of every kind of signal type.
2. the shelf depreciation PRPS spectrum recognition method according to claim 1 based on hierarchical rule reasoning, feature exist
In the step 1 includes: specifically to be made by the local discharge signal that a variety of partial discharge detector's devices acquire power equipment
With the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit, the local discharge signal of power equipment is detected, is remembered
Record PRPS map.
3. the shelf depreciation PRPS spectrum recognition method according to claim 1 based on hierarchical rule reasoning, feature exist
In the step 2 includes:
Step 2.1: PRPS spectrum data being normalized, by electric discharge amplitude reduction into [0,1] section；Normalization meter
The method of calculation is as follows:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates the minimum value in amplitude measurement section,
Max indicates the maximum value in amplitude test section；
The denoising of step 2.2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS distribution of pulses number
Incidence relation between, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, throughout
Small threshold value ambient noise refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Step 2.3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method, makes letter
Number the first, second, third and fourth quadrant of discharge phase distribution have complete characterization；Wherein, adaptive phase adjusting method refers to basis
Distribution of the PRPS map in phase, adjust automatically phase offset；
Step 2.4:PRPS characteristic parameter extraction, count PRPS map discharge time phase distribution, electric discharge amplitude phase distribution,
Discharge time period profile obtains discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree and divides
These PRPS characteristic parameters of divergence.
4. a kind of shelf depreciation PRPS spectrum recognition system based on hierarchical rule reasoning characterized by comprising
Detection module obtains PRPS map for detecting the local discharge signal of power equipment；
Data processing module obtains PRPS characteristic parameter for handling PRPS spectrum data；
Diagnostic module, for being analyzed by hierarchical rule reasoning diagnostic system PRPS characteristic parameter, judgement obtains electric power
The shelf depreciation type of equipment；
Wherein, the diagnostic module includes: the PRPS characteristic parameter input hierarchical rule reasoning diagnostic system that will be obtained, and is exported
To the confidence level of every kind of signal type, diagnosis is obtained after statistics；
The hierarchical rule reasoning diagnostic system includes: foundation characteristic layer, linked character layer, signal characteristic layer and signal type
Layer；
The foundation characteristic layer is used to characterize the foundation characteristic of map；Foundation characteristic includes: number of signals section, signal sub-clustering
Number, the electric discharge degree of correlation, electric discharge amplitude fluctuations parameter；
The linked character layer, for doing association analysis according to the similitude of each foundation characteristic；
The signal characteristic layer is for storing the performance of multi-signal feature, i.e., there are many signal characteristics to show for every class signal, and every kind
Signal characteristic is the combination of linked character layer association analysis result；
The signal type layer meets situation, output for sequentially judge signal characteristic in input signal and signal characteristic layer
The confidence level of every kind of signal type.
5. the shelf depreciation PRPS spectrum recognition system according to claim 4 based on hierarchical rule reasoning, feature exist
In the detection module includes: the local discharge signal for acquiring power equipment by a variety of partial discharge detector's devices, specifically
The shelf depreciation letter of power equipment is detected using the superfrequency of instrument for measuring partial discharge, ultrasound and high-frequency current detection unit in ground
Number, record PRPS map.
6. the shelf depreciation PRPS spectrum recognition system according to claim 4 based on hierarchical rule reasoning, feature exist
In the data processing module includes:
Submodule 1: being normalized PRPS spectrum data, by electric discharge amplitude reduction into [0,1] section；Normalization meter
The method of calculation is as follows:
Wherein, x indicates that, to normalized amplitude, y indicates the amplitude after normalization, and min indicates the minimum value in amplitude measurement section,
Max indicates the maximum value in amplitude test section；
The denoising of submodule 2:PRPS spectrum data, removes ambient noise and scattered interference signal；I.e. according to PRPS distribution of pulses number
Incidence relation between, remove random interfering signal, and to throughout small threshold value ambient noise filter out；Wherein, throughout
Small threshold value ambient noise refers to the ambient noise for being different from local discharge characteristic, and amplitude is less than specified threshold；
Submodule 3:PRPS phase alignment；Specifically, phase alignment is done to PRPS map with adaptive phase adjusting method, makes letter
Number the first, second, third and fourth quadrant of discharge phase distribution have complete characterization；Wherein, adaptive phase adjusting method refers to basis
Distribution of the PRPS map in phase, adjust automatically phase offset；
Submodule 4:PRPS characteristic parameter extraction, count PRPS map discharge time phase distribution, electric discharge amplitude phase distribution,
Discharge time period profile obtains discharge time, degree of skewness, standout, degree of asymmetry, related coefficient, pulse concentration degree and divides
These PRPS characteristic parameters of divergence.
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| CN106526434A (en) * | 2016-10-11 | 2017-03-22 | 国网上海市电力公司 | Partial discharge mode identifying method and device |
| CN106950480A (en) * | 2017-04-28 | 2017-07-14 | 上海欧忆能源科技有限公司 | The online qualitative checking method of power equipment shelf depreciation, system and equipment |
| CN107656177B (en) * | 2017-08-18 | 2019-07-12 | 西安交通大学 | Based on shelf depreciation or SF6The dry sleeve insulation defect diagnostic method of decomposition product |
| CN108333443B (en) * | 2017-12-22 | 2020-08-25 | 国家电网公司 | Method for alarming intermittent defects of power equipment |
| CN108919068B (en) * | 2018-06-07 | 2021-09-14 | 国网宁夏电力有限公司电力科学研究院 | Intermittent defect signal identification method for power equipment |
| CN109188211B (en) * | 2018-07-30 | 2021-02-05 | 上海交通大学 | High-voltage equipment insulation fault diagnosis method and system |
| CN110658433B (en) * | 2019-11-08 | 2020-09-25 | 广东电网有限责任公司 | Method for enhancing PRPS (partial discharge protection period) atlas sample |
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